63 citations · 64 across the 5 of their papers we have counts for
5 papers
Cascading and Proxy Membership Inference Attacks
Yuntao Du, Jiacheng Li, Yuetian Chen +5
A Membership Inference Attack (MIA) assesses how much a trained machine learning model reveals about its training data by determining whether specific query instances were included…
MIST: Defending Against Membership Inference Attacks Through Membership-Invariant Subspace Training
Jiacheng Li, Ninghui Li, Bruno Ribeiro
In Member Inference (MI) attacks, the adversary try to determine whether an instance is used to train a machine learning (ML) model. MI attacks are a major privacy concern when usi…
SmartBERT: A Promotion of Dynamic Early Exiting Mechanism for Accelerating BERT Inference
Boren Hu, Yun Zhu, Jiacheng Li +1
Dynamic early exiting has been proven to improve the inference speed of the pre-trained language model like BERT. However, all samples must go through all consecutive layers before…
Deep Learning for Logo Detection: A Survey
Sujuan Hou, Jiacheng Li, Weiqing Min +4
When logos are increasingly created, logo detection has gradually become a research hotspot across many domains and tasks. Recent advances in this area are dominated by deep learni…
Membership Inference Attacks and Defenses in Classification Models
Jiacheng Li, Ninghui Li, Bruno Ribeiro
We study the membership inference (MI) attack against classifiers, where the attacker's goal is to determine whether a data instance was used for training the classifier. Through s…